Jesper Kristensen

Context-based Sales and Operations Planning (S&OP) research: A literature review and future agenda

Purpose – This paper’s purpose was to describe and categorize how current literature contributes to S&OP research on how contextual variables affect S&OP design and to frame future areas for context-based S&OP research. Design/methodology/approach – The method used was a systematic literature review. Studies for review were obtained through a keyword search of five relevant databases, manual searches of relevant journals and snowballing of citations in relevant papers. In total, 571 papers published between 2000 and 2017 were assessed, and 68 papers were included in the review. Findings – The review found that S&OP design depends on industry, dynamic complexity, detail complexity and organisational characteristics. The findings of the literature review suggest that future research should study the roles of industry, complexity, system and process and organisational characteristics in S&OP design. Research implications – The findings revealed several gaps in the literature on context-dependent S&OP design. To address these gaps, an agenda for future S&OP contingency research is developed. Practical implications – The findings revealed which contextual areas and specific S&OP design issues must be considered when designing and implementing S&OP. Originality/values – This study focused on identifying relevant research on S&OP design by analysing the contribution of literature to a research framework inspired by contingency based research of operations and supply chain management.

Outsourcing of production: the valuation of volume flexibiltiy in decision-making

Background: Outsourcing remains a central mechanism for improving manufacturing supply chains, with volume flexibility being a frequently targeted objective. However, outsourcing decision-making remains focused on static cost estimations, while the value of volume flexibility is subject to managerial valuation, thus imposing a risk of estimation errors. This paper tests whether decision-makers systematically underor overvalue volume flexibility when deciding on outsourcing. Methods: Four outsourcing decision made by an OEM operating with seasonality and boom and bust cycles are analyzed to assess if decision-makers’ intrinsic valuation of volume flexibility is biased. This was done by utilizing a previously developed mixed integer linear programming model for tactical planning. The model jointly considers production planning, workforce adjustments and capital investment, while respecting upstream supplier constraints, thereby encompassing both positive and negative effects of production outsourcing on volume flexibility. Combining the model with detailed knowledge of how the production system would be impacted, enabled a quantification of the value from volume flexibility, which could then be compared to the decisions made. Results: Augmenting existing static cost estimations with the value of flexibility did not reveal systematic estimation errors. However, the results suggest that the value of volume flexibility is situational, and on average comparable to direct labor cost. Conclusions: The results emphasize the importance of accurately and case-specific valuation of volume flexibility in cost-driven production outsourcing.

When to integrate strategic and tactical decisions? Introduction of an asset/inventory ratio guiding fit for purpose production planning

Purpose Significant transitions in firms (e.g. outsourcing) may impact the relative importance of production and inventory assets, affecting the hierarchical separation of planning decisions. The purpose of this paper is to contribute to planning literature by investigating how the production system and the planning environment influence the performance difference between hierarchical and monolithic planning. Further, it seeks to reduce the prevailing theory-practice gap in tactical planning. Design/methodology/approach Through an action research study, a monolithic model integrating tactical production planning decisions, subject to upstream supply chain constraints, with strategic investments decisions was developed, tested and implemented in a global OEM. Using the developed model and a measure of the capital cost of production assets relative to the cost of holding inventory, it is numerically examined how the production system and planning environment influence the performance of hierarchical and monolithic planning. Findings The research demonstrates the potential of integrating decisions and reveals significant performance differences between hierarchical and monolithic planning for firms with low capital cost relative to inventory holding cost. Research limitations/implications The findings suggest a fit between planning processes, the production system and planning environment. Future research should empirically validate the findings and propositions. Originality/value The paper combine capital investments and production planning decisions, which usually transpire at different hierarchical levels and on different time-horizons, and investigates the consequences of hierarchical separation through a real-life validated case and numerical analysis.

The Link Between Supply Chain Design Decision-Making and Supply Chain Complexity: An Embedded Case Study

This paper presents a conceptual model of the supply chain characteristics leading to supply chain complexity. This is combined with the change complexity of supply chain improvements, to reflect the complexity found in supply chain design decision-making when improving global supply chains. These two dimensions are used empirically, in the investigation of eight embedded cases of supply chain re-design, in a global OEM. Three contributions are made, improving the understanding of the link between supply chain design decision-making and supply chain complexity. First, the impact of different types of supply chain complexity on decision-making. Detail complexity leads to a higher need for resources for data collection and analysis, while dynamic complexity leads to challenges in predicting future performance. Second, the degree of change complexity is determining the potential supply chain complexity reduction. Third, a systematic bias resulting from low transparency on the marginal impact of increasing or decreasing supply chain complexity is proposed to lead to increasing supply chain complexity.